| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 37 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 74 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1617 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 80.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 53.62% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1617 | | totalAiIsms | 15 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | word | "carried the weight" | | count | 1 |
| | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | |
| | highlights | | 0 | "gloom" | | 1 | "standard" | | 2 | "stark" | | 3 | "echoing" | | 4 | "marble" | | 5 | "etched" | | 6 | "carried the weight" | | 7 | "weight" | | 8 | "perfect" | | 9 | "shimmered" | | 10 | "predator" | | 11 | "familiar" | | 12 | "silence" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 0 | | maxInWindow | 0 | | found | (empty) | | highlights | (empty) | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 126 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 126 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 162 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 40 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 3 | | markdownWords | 12 | | totalWords | 1605 | | ratio | 0.007 | | matches | | 0 | "British Museum - Restricted Archives." | | 1 | "Item: tablet fragment 44-B." | | 2 | "Requestor: E. Kowalski." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 20 | | unquotedAttributions | 0 | | matches | (empty) | |
| 16.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 76 | | wordCount | 1155 | | uniqueNames | 21 | | maxNameDensity | 2.6 | | worstName | "Quinn" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Quinn" | | discoveredNames | | Patel | 9 | | Detective | 1 | | Harlow | 1 | | Quinn | 30 | | Camden | 3 | | Miller | 13 | | Morris | 3 | | Veil | 1 | | Market | 1 | | Museum | 2 | | Restricted | 1 | | Kowalski | 2 | | Aurora | 1 | | Shoreditch | 1 | | London | 1 | | High | 1 | | Street | 1 | | Doc | 1 | | Martens | 1 | | Ford | 1 | | Maglite | 1 |
| | persons | | 0 | "Patel" | | 1 | "Harlow" | | 2 | "Quinn" | | 3 | "Miller" | | 4 | "Morris" | | 5 | "Museum" | | 6 | "Kowalski" |
| | places | | 0 | "Camden" | | 1 | "London" | | 2 | "High" | | 3 | "Street" |
| | globalScore | 0.201 | | windowScore | 0.167 | |
| 57.41% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 81 | | glossingSentenceCount | 3 | | matches | | 0 | "looked like ink had been pumped through h" | | 1 | "spiral that seemed to turn inward on itself" | | 2 | "looked like a woman who had dispensed wit" |
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| 75.39% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.246 | | wordCount | 1605 | | matches | | 0 | "not cut, but erased" | | 1 | "Not against a knife, but against" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 162 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 80 | | mean | 20.06 | | std | 14.2 | | cv | 0.708 | | sampleLengths | | 0 | 4 | | 1 | 33 | | 2 | 7 | | 3 | 51 | | 4 | 6 | | 5 | 30 | | 6 | 36 | | 7 | 36 | | 8 | 42 | | 9 | 3 | | 10 | 21 | | 11 | 24 | | 12 | 12 | | 13 | 37 | | 14 | 4 | | 15 | 47 | | 16 | 30 | | 17 | 27 | | 18 | 5 | | 19 | 2 | | 20 | 23 | | 21 | 38 | | 22 | 7 | | 23 | 22 | | 24 | 5 | | 25 | 7 | | 26 | 4 | | 27 | 1 | | 28 | 25 | | 29 | 43 | | 30 | 34 | | 31 | 12 | | 32 | 8 | | 33 | 48 | | 34 | 4 | | 35 | 4 | | 36 | 1 | | 37 | 43 | | 38 | 9 | | 39 | 8 | | 40 | 17 | | 41 | 14 | | 42 | 4 | | 43 | 38 | | 44 | 21 | | 45 | 23 | | 46 | 34 | | 47 | 2 | | 48 | 18 | | 49 | 10 |
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| 91.34% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 126 | | matches | | 0 | "were contorted" | | 1 | "been pumped" | | 2 | "was flayed" | | 3 | "was found" | | 4 | "been hollowed" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 208 | | matches | | |
| 1.76% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 9 | | semicolonCount | 0 | | flaggedSentences | 8 | | totalSentences | 162 | | ratio | 0.049 | | matches | | 0 | "The air here was thicker, heavy with the metallic tang of dried blood and something else—something sweet and cloying, like burnt sugar." | | 1 | "She adjusted the worn leather watch on her wrist—a nervous tick—and leaned in." | | 2 | "Etched into the surface was a symbol that made her eyes water if she focused on it too long—a spiral that seemed to turn inward on itself." | | 3 | "She had seen sketches of it in Morris's notes—the ones he’d hidden under his floorboards." | | 4 | "The skin of the victim's back was flayed—not cut, but erased." | | 5 | "*British Museum - Restricted Archives.*" | | 6 | "Tourists, punks, shoppers—all oblivious to the fact that ten meters below their Doc Martens, a man had been hollowed out like a pumpkin." | | 7 | "Beside her, on the passenger seat, lay her heavy Maglite and a pair of iron handcuffs—cold iron, specially forged." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1167 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 26 | | adverbRatio | 0.022279348757497857 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.003427592116538132 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 162 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 162 | | mean | 9.91 | | std | 6.96 | | cv | 0.702 | | sampleLengths | | 0 | 4 | | 1 | 5 | | 2 | 14 | | 3 | 14 | | 4 | 7 | | 5 | 11 | | 6 | 14 | | 7 | 16 | | 8 | 10 | | 9 | 6 | | 10 | 23 | | 11 | 7 | | 12 | 11 | | 13 | 18 | | 14 | 7 | | 15 | 25 | | 16 | 11 | | 17 | 5 | | 18 | 22 | | 19 | 15 | | 20 | 3 | | 21 | 21 | | 22 | 7 | | 23 | 17 | | 24 | 5 | | 25 | 7 | | 26 | 14 | | 27 | 23 | | 28 | 4 | | 29 | 12 | | 30 | 15 | | 31 | 20 | | 32 | 22 | | 33 | 8 | | 34 | 5 | | 35 | 9 | | 36 | 13 | | 37 | 5 | | 38 | 2 | | 39 | 16 | | 40 | 7 | | 41 | 4 | | 42 | 18 | | 43 | 6 | | 44 | 10 | | 45 | 7 | | 46 | 22 | | 47 | 5 | | 48 | 7 | | 49 | 4 |
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| 81.69% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.5123456790123457 | | totalSentences | 162 | | uniqueOpeners | 83 | |
| 30.86% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 108 | | matches | | 0 | "Just charred meat and that" |
| | ratio | 0.009 | |
| 82.96% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 37 | | totalSentences | 108 | | matches | | 0 | "He jerked back, grimacing as" | | 1 | "he hissed, shaking his hand" | | 2 | "She marched down the incline," | | 3 | "He looked as tired as" | | 4 | "He held a clipboard like" | | 5 | "It tickled the back of" | | 6 | "She pushed the memory down," | | 7 | "She approached the body." | | 8 | "He was naked, his skin" | | 9 | "His limbs were contorted, twisted" | | 10 | "She adjusted the worn leather" | | 11 | "It looked like ink had" | | 12 | "She turned her beam to" | | 13 | "She walked to the edge" | | 14 | "She held the bag up" | | 15 | "It was a token, carved" | | 16 | "She pocketed the bag" | | 17 | "She knew what this was." | | 18 | "She had seen sketches of" | | 19 | "She turned back to the" |
| | ratio | 0.343 | |
| 24.81% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 94 | | totalSentences | 108 | | matches | | 0 | "The warning came too late." | | 1 | "Constable Patel’s gloved hand had" | | 2 | "He jerked back, grimacing as" | | 3 | "he hissed, shaking his hand" | | 4 | "Detective Harlow Quinn didn't break" | | 5 | "She marched down the incline," | | 6 | "The torch in her left" | | 7 | "Quinn stopped at the police" | | 8 | "DS Miller detached himself from" | | 9 | "He looked as tired as" | | 10 | "He held a clipboard like" | | 11 | "Miller gestured behind him with" | | 12 | "Quinn ducked under the tape." | | 13 | "The air here was thicker," | | 14 | "It tickled the back of" | | 15 | "She pushed the memory down," | | 16 | "Quinn repeated, her voice flat" | | 17 | "Quinn pointed her torch at" | | 18 | "She approached the body." | | 19 | "The victim was male, mid-twenties," |
| | ratio | 0.87 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 108 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 42 | | technicalSentenceCount | 2 | | matches | | 0 | "His limbs were contorted, twisted at angles that suggested his bones had turned to liquid before snapping back into rigidity." | | 1 | "The alcove was circular, lined with old electrical junction boxes that hummed with a frequency that made her fillings ache." |
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| 57.43% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 37 | | uselessAdditionCount | 5 | | matches | | 0 | "Quinn repeated, her voice flat" | | 1 | "Miller sighed, the sound echoing wetly in the tunnel" | | 2 | "Quinn stood up, her knees cracking" | | 3 | "she said, her voice low" | | 4 | "Quinn called back, her stride lengthening" |
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| 14.86% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 20 | | fancyCount | 10 | | fancyTags | | 0 | "he hissed (hiss)" | | 1 | "Quinn repeated (repeat)" | | 2 | "Miller sighed (sigh)" | | 3 | "Quinn murmured (murmur)" | | 4 | "Quinn barked (bark)" | | 5 | "Quinn muttered (mutter)" | | 6 | "Quinn corrected (correct)" | | 7 | "Quinn whispered (whisper)" | | 8 | "Quinn called back (call back)" | | 9 | "she muttered (mutter)" |
| | dialogueSentences | 74 | | tagDensity | 0.27 | | leniency | 0.541 | | rawRatio | 0.5 | | effectiveRatio | 0.27 | |